Sparse reconstruction inspired by compressed sensing has attracted considerable attention in fluorescence molecular tomography (FMT). However, the columns of system matrix used for FMT reconstruction tend to be highly coherent, which means L1 minimization may not produce the sparsest solution. In this paper, we propose a novel reconstruction method by minimization of the difference of L1 and L2...

Because an electric scooter driven by permanent magnet synchronous motor (PMSM) servo-driven system has the unknown nonlinearity and the time-varying characteristics, its accurate dynamic model is difficult to establish for the design of the linear controller in whole system. In order to conquer this difficulty and raise robustness, a novel adaptive modified recurrent Legendre neural network (N...

Adaptive flight control is a potentially promising technology that can improve aircraft stability and maneuverability. In recent years, adaptive control has been receiving a significant amount of attention. In aerospace applications, adaptive control has been demonstrated in many flight vehicles. For example, NASA has conducted a flight test of a neural net intelligent flight control system on ...

Radiotherapy is a major part in the treatment of most common cancers, but many patients experience local recurrence with metastatic disease. In evaluating response biomarkers, we found that low doses of fractionated radiotherapy led to PD-L1 upregulation on tumor cells in a variety of syngeneic mouse models of cancer. Notably, fractionated radiotherapy delivered in combination with αPD-1 or αPD...

Rationale: TCR-T cell therapy plays a critical role in the treatment of malignant cancers. However, it is unclear how cells are affected by PD-L1 molecule tumor environment. We performed an in-depth evaluation on differential expressions can affect functionality T cells. Methods: used MART-1-specific (TCR-TMART-1), stimulated with MART-127-35 peptide-loaded MEL-526 cells, expressing different p...

This paper describes a novel technique for promoting sparsity in the modified filtered-x algorithms required for active noise control. The proposed algorithms are based on recent techniques incorporating approximations to the l0-norm in the cost functions that are used to derive adaptive filtering algorithms. In particular, zero-attracting and reweighted zeroattracting filtered-x adaptive algor...

We propose a sequential quadratic programming (SQP) method for the optimal control of large-scale dynamical systems. The method uses modified multiple shooting to discretize the dynamical constraints. When these systems have relatively few parameters, the computational complexity of the modified method is much less than that of standard multiple shooting. Moreover, the proposed method is demons...

One important goal of regression analysis is prediction. In recent years, the idea of combining different statistical methods has attracted an increasing attention. In this work, we propose a method, l1-ARM (adaptive regression by mixing), to robustly combine model selection methods that performs well adaptively. In numerical work, we consider the LASSO, SCAD, and adaptive LASSO in representati...

In this work we investigate the possibility of applying the adaptive control algorithm to Micro-Electro-Mechanical System (MEMS) gyroscopes. Through comparing the gyroscope working conditions with the reference model, the adaptive control method can provide online estimation of the key parameters and the proper control strategy for the system. The digital second-order oscillators in the referen...

In order to improve the safety and longitudinal stability of a vehicle equipped with standard ABS system, this paper, analyzes the basic principles of vehicles stability and proposes a control strategy based on fuzzy adaptive control which will adjust PID gain parameters, using genetic algorithm. A linear three-degree-of-freedom (DOF) vehicle model was set up in Simulink and the stability test ...